Marketing Analyst, New Business and M&A

Accountabilities:

Build and maintain marketing data infrastructure: Develop and manage end-to-end data systems that connect advertising impressions, clicks, lead acquisition, engagement, and revenue, integrating Google Analytics, Google Ads, and other relevant marketing platforms.

Integrate newly acquired businesses: Rapidly assess and incorporate the marketing data infrastructure of acquired companies, establishing reliable tracking, attribution, reporting, and measurement standards.

Analyze advertising performance: Evaluate paid acquisition channels and campaigns using metrics such as customer acquisition cost (CAC), return on advertising spend (ROAS), customer lifetime value (LTV), funnel conversion, and payback periods to optimize marketing investments.

Develop analytical models and forecasts: Use SQL, statistical analysis, predictive modeling, and hypothesis testing to identify performance drivers, forecast outcomes, diagnose issues, and evaluate potential improvements.

Create dashboards and performance reports: Build and maintain clear, actionable reporting solutions using business intelligence tools such as Tableau, Power BI, or Qlik to support marketing teams and business leaders.

Define and standardize performance metrics: Establish consistent, accurate, and strategically aligned definitions for LTV, ROAS, CAC, and other key indicators across businesses to improve comparability and decision-making.

Translate data into business recommendations: Conduct descriptive and diagnostic analyses, identify root causes, and communicate the business implications of findings through practical recommendations that improve marketing efficiency and financial performance.

Collaborate across business functions: Work closely with business analysts focused on new ventures and acquisitions, connecting marketing performance with revenue, unit economics, operational effectiveness, and broader business objectives.

Map marketing processes and data flows: Understand how marketing activities translate into data across acquisition, engagement, conversion, and revenue generation, identifying gaps and opportunities for improvement.

Identify opportunities for optimization: Proactively recommend improvements in campaign efficiency, conversion rates, revenue generation, customer and talent experience, operational processes, communication, systems, and resource allocation.

Leverage AI and automation: Use generative AI tools to accelerate analytical work, automate reporting workflows, and improve the scalability and efficiency of marketing analytics.

Support strategic business decisions: Provide insights that inform marketing budgets, channel strategies, business priorities, performance targets, and long-term growth initiatives.

Build a repeatable M&A analytics framework: Develop standardized processes and playbooks for integrating marketing data from acquired companies and continuously improving measurement capabilities.

Requirements:

Education: Bachelor's degree in a relevant field is required. A background in mathematics, statistics, science, finance, or engineering is highly valuable. An advanced degree or MBA is an advantage.

Professional experience: At least three years of experience in data analysis, business intelligence, or analytics, with a strong focus on marketing performance.

Paid media analytics: Demonstrated experience evaluating paid advertising campaigns, including Google Ads and other paid media platforms, and translating campaign performance into metrics such as CAC, LTV, ROAS, and payback.

Marketing data infrastructure: Hands-on experience building or managing tracking systems, attribution models, data pipelines, and marketing reporting infrastructure.

Google ecosystem expertise: Strong technical knowledge of Google Analytics, Google Ads, and related data integrations, with the ability to work across different marketing platforms and business environments.

Business intelligence tools: Experience developing dashboards and reports using Tableau, Power BI, Qlik, or comparable analytics platforms.

Technical proficiency: Strong SQL skills are required. Experience with Python, R, or MATLAB is an advantage.

Analytical and statistical skills: Working knowledge of probability, statistics, exploratory data analysis, hypothesis testing, root cause analysis, forecasting, predictive modeling, and performance measurement.

Generative AI experience: Practical experience using tools such as ChatGPT, Claude, or Gemini to support analysis, automate workflows, and improve reporting efficiency.

Business-oriented problem-solving: Proven ability to connect analytical findings with marketing strategy, financial performance, and operational outcomes, turning complex data into measurable business impact.

Process improvement: Experience mapping business processes, identifying inefficiencies, and developing scalable analytical frameworks is beneficial.

Startup and M&A exposure: Experience working with startups, early-stage businesses, newly launched ventures, or post-acquisition integrations is a plus.

Stakeholder management: Ability to build productive relationships across teams, manage competing priorities, and collaborate effectively in a fast-paced, evolving environment.

Communication skills: Excellent written and verbal communication skills, with the ability to explain complex analytical concepts clearly, challenge assumptions constructively, and communicate data limitations and potential blind spots.

Ownership and execution: A proactive, hands-on approach, strong attention to detail, sound judgment, and the ability to manage multiple projects and deadlines independently.

Remote collaboration: Ability to work effectively with globally distributed teams and communicate professionally in English. Applications and related communication must be submitted in English.

Work authorization: This is a remote position; visa sponsorship or immigration assistance is not provided.

Benefits:

Fully remote work: Work remotely within the eligible geographic locations, collaborating with an international team across Europe, South America, and Central America.

Global exposure: Contribute to analytics initiatives spanning new business ventures and acquired companies, gaining insight into diverse business models, marketing strategies, and operational environments.

Strategic impact: Influence acquisition spending, channel strategy, financial performance, and business growth through data-driven recommendations.

Professional development: Build expertise across marketing analytics, business intelligence, data infrastructure, forecasting, and M&A integration.

Technical ownership: Take responsibility for designing and improving analytical systems, reporting frameworks, and scalable measurement processes.

AI-driven innovation: Work with modern generative AI tools and automation techniques to improve analytical productivity and reporting capabilities.

Cross-functional collaboration: Partner with business analysts, marketing leaders, and operational teams to solve complex challenges and deliver measurable results.

Career growth opportunities: Develop your capabilities in a fast-moving, global organization where independent contribution, initiative, and continuous improvement are highly valued.

Note: Specific compensation, healthcare coverage, paid leave, and additional benefits were not detailed in the source job description.